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Artificial neural networks are inspired by biologic processes. Artificial neural networks are important because they can be used to deduct a function from observations, in other words artificial neural networks can learn from experience. Artificial neural network simulator to fulfill a need into the growing interest of neural network education is introduced in this study. NeuroQuick Laboratory simulator is implemented using object-oriented programming by Delphi programming and these classes can be used to create a standalone application with artificial neural networks. The NeuroQuick Laboratory Simulator is designed for a broad range of users, including beginning graduate/advanced undergraduate students, engineers, and scientists. It is particularly well-suited for use in individual student projects or as a simulation tool in one- or two-semester neural network-related courses at universities. [ABSTRACT FROM AUTHOR]

Artificial neural networks, inspired by the biological networks of the human brain, have become game-changing computing models in modern computer science. Inspired by their wide scope of applications, synthetic biology strives to create their biological counterparts, which we denote synthetic biological neural networks (SYNBIONNs). Their use in the fields of medicine, biosensors, biotechnology, and many more shows great potential and presents exciting possibilities. So far, many different synthetic biological networks have been successfully constructed, however, SYNBIONN implementations have been sparse. The latter are mostly based on neural networks pretrained in silico and being heavily dependent on extensive human input. In this paper, we review current implementations and models of SYNBIONNs. We briefly present the biological platforms that show potential for designing and constructing perceptrons and/or multilayer SYNBIONNs. We explore their future possibilities along with the challenges that must be overcome to successfully implement a scalable in vivo biological neural network capable of online learning. [ABSTRACT FROM AUTHOR]